Data
6 min read

The Power of Active, Timestamp, and Lookback Data in GTM Strategies

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Lindsey Meyl
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One of the bigger challenges we have in Revenue Operations is that we have to custom-build most of the infrastructure needed to run the go-to-market. Part of the reason I'm so bullish on the frameworks that Pavilion, Winning by Design, and GTM Partners are evangelizing is that they eliminate the need to custom-build everything.

Case in point: There are three different types of data categories you need to build to run your GTM operating model.

💻 Active Data

⏳ Timestamp Data

💡 Lookback Data

Active Data

Active Data is the data most often provided by the CRM, which is the relevant information and interactions you had with a customer. This type of data provides the current volume of all the data objects tied to the applicable milestones in your GTM framework. Examples of active data are:

  • How much open pipeline do you have over a specific period? 
  • What leads need to be contacted?
  • How many customers are going through implementation? 

Active data is often captured through fields and objects in a CRM. The problem with this type of data is that it only tells you the status of what is currently happening. The moment something new happens, your active data updates to that new state. Therefore, you lose the information that tells you how the customer got to that current state.

I don't think we talk enough about the additional buildouts across a tech stack required to capture the critical data needed to evaluate the performance of your GTM. 

So, what other types of data do you need to drive insights for your business? 

Timestamp Data

Timestamp Data is the metadata that tells you exactly when something happened. This chronological record is crucial in various applications, from organizing your GTM frameworks to understanding the sequence of actions and analyzing patterns over time. It's like putting each piece of data in its time capsule for future reference.

Timestamp Data provides:

  • Performance Analysis: Timestamp Data facilitates the analysis of performance metrics over time. It helps you assess volume, conversion, and time performance across your GTM operating model and provides visibility into your organization's overall efficiency.
  • Activity History: Timestamps create a timeline of customer activities, providing a historical perspective. This can be essential for tracking the evolution of customer relationships and identifying trends. 
  • Communication Tracking: Timestamps on visits, clicks, calls, and meetings enable users to see when each interaction occurred. This is valuable for understanding communication patterns and ensuring timely follow-ups.
  • Audit Trails: Timestamps contribute to the creation of audit trails, providing a detailed account of what data in your system changed and when. Audit trails are significant for accountability in assignments, routing, and general data integrity.

Timestamp Data is the chronological backbone, offering a structured way to understand, analyze, and improve the dynamics of customer interactions and business processes across your GTM operating model. 

Timestamping is essential, and we must acknowledge how ill-equipped the CRM is to manage this type of Timestamp Data. 

You may have come across timestamping processes in the past by identifying the ‘Pipe Gen’ date, which captures when an opportunity moves from one stage to another. Sales stage stamps are a fine place to start, but without building out further timestamp events, you’ll never get a complete picture of how a customer as an individual, company, and deal truly progresses. This is precisely why so many have struggled to build Winning by Design’s Data Model framework.

The only way to collect Timestamp Data across people, companies, deals, and activities in a CRM is to build custom objects with individually built workflows for each event you want to stamp. But there are enormous tradeoffs because it’s a massive project with endless workflow builds, and anytime you want to change or update the timestamp trigger criteria, you’ll have to rebuild the workflow.

The other enormous gap is the limitations on what type of data you can bring into your CRM. Thus, the criteria that define the timestamp workflows will be subject to factors such as the date a field was updated. This introduces errors and bias into your performance metrics. 

Long story short, I’ve spent years trying to get the CRM to manage Timestamp Data, and I’m convinced it’s not possible beyond simple field update use cases. I’m dying to hear from someone who has managed this, so please speak up! 

This takes us to why we collect data in the first place, which is… 

Lookback Data

Lookback Data takes the historical data you created through timestamps and other data collection methods. Then, it retrospectively examines your data to gain insights, identify patterns, and understand trends.

While timestamping reports the news, Lookback Data tells you to see why it happened and what you can do about it.

Lookback Data provides:

  • Customer Segmentation: Segment your B2B customers more effectively. Tailor your marketing and outreach based on what worked in the past.
  • Product Development: Understand the features or solutions clients found most valuable, then focus on enhancing or creating similar offerings.
  • Optimizing Processes: Identify the most successful approaches and strategies from the past, refine them, and make them more efficient and targeted.
  • Predictive Analytics: Use historical data to build predictive models. Predict future trends, customer behavior, and market shifts, enabling your team to be proactive in their approach.
  • Messaging: Analyze the performance of past content to understand what resonates best with your audience. Tailor your content strategy to address the pain points or interests that have historically engaged your B2B customers.
  • Customer Retention: Lookback Data can reveal patterns associated with customer churn. By understanding why customers left in the past, you can implement retention strategies to prevent future losses.
  • Market Expansion: Evaluate past successes in entering new markets. Identify the factors contributing to successful expansions and apply those insights to future market entry strategies.

Lookback Data turns raw data into actionable insights, giving you the answers you need about your organization to inform decision-making and strategy. 

These are the GTM data pillars leveraged by Revenue Operations. But to return to the original point, why do we require RevOps to custom-build this data infrastructure? No wonder it can take months, if not years, to get answers to important go-to-market questions. 

If we start mirroring these standard GTM frameworks to this data infrastructure, we eliminate the custom build, maintenance, and fixes. And then we can simply get to decisions and execution, which is the whole point anyway.

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